Sr. DevOps Engineer

Sr. DevOps Engineer Location: India, Hyderabad (Hybrid)

Work Experience: 5-8 Years

• Hands-on experience in platform, infrastructure, or SRE with at least 3 years focused on cloud infrastructure or developer platforms.
• Expertise in cloud-native architecture: Kubernetes at scale, managed cloud services, networking, identity federation, and multi-tenancy patterns across AWS, GCP, or Azure.
• Proven ownership of complex, multi-month platform initiatives; you have part of them from whiteboard to production, managing ambiguity and technical risk throughout.
• Proficient in IaC and GitOps fluency - Terraform or Pulumi, ArgoCD with experience standardising platform tooling and deployment patterns across engineering teams.
• Hands-on experience with AI/ML infrastructure: model serving, inference pipelines, GPU resource management, or LLM integration patterns.
• Experience in enterprise environments with familiarity with compliance frameworks such as SOC 2, ISO 27001, or GDPR.
• Strong written communication; you write clear design docs, maintain useful ADRs, and can explain architectural decisions to both engineers and non-technical stakeholders.

Nice to Have:

• LLM serving at scale - vLLM, Triton, Ray Serve or AI gateway design patterns.
• You treat platform as a product and obsess over internal developer experience.
• FinOps or GPU cost optimisation across large inference workloads.
• You default to writing things down and creating shared technical context.
• Building an internal developer platform (IDP) from scratch.
• You push back on short-term thinking and advocate for the right long-term call.
• Open-source contributions to platform or ML infrastructure tooling.
• You are energised by ambiguity and build clarity where there isn t any.

Qualifications: Bachelors or Masters degree in Computer Science, Information Technology, or a related field.

• Lead the design and architecture of cloud-native platforms, manage Kubernetes at scale (AWS/GCP/Azure), including networking, identity federation, and multi-tenancy setups.
• Own complex, multi-month platform initiatives end-to-end, from whiteboard design through production rollout, managing ambiguity and technical risk along the way.
• Define and standardise IaC (Terraform/Pulumi) and GitOps (ArgoCD) practices to ensure consistent deployment patterns across engineering teams.
• Build and maintain AI/ML infrastructure, design scalable systems for model serving, inference pipelines, GPU resource management, and LLM integration.
• Ensure enterprise-grade compliance by aligning platform architecture with frameworks such as SOC 2, ISO 27001, and GDPR.
• Write and maintain clear design docs and ADRs (Architecture Decision Records), communicating architectural decisions effectively to both engineers and non-technical stakeholders.
• Treat the internal developer platform (IDP) as a product, continuously iterate to improve developer experience and adoption.
• Collaborate cross-functionally to standardise platform tooling and drive its adoption across teams.
• Explore and implement LLM serving frameworks (vLLM, Triton, Ray Serve) or AI gateway design patterns where applicable.
• Drive GPU cost optimisation and FinOps practices for large-scale inference workloads.
• Champion a culture of documentation and shared technical context across the team.